{
  "cells": [
{
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hinabl/voice-changer-colab/blob/master/Hina_Modified_Realtime_Voice_Changer_on_Colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Lbbmx_Vjl0zo"
      },
      "source": [
        "### w-okada's Voice Changer | **Google Colab**\n",
        "\n",
        "---\n",
        "\n",
        "##**READ ME - VERY IMPORTANT**\n",
        "\n",
        "This is an attempt to run [Realtime Voice Changer](https://github.com/w-okada/voice-changer) on Google Colab, still not perfect but is totally usable, you can use the following settings for better results:\n",
        "\n",
        "If you're using a index: `f0: RMVPE_ONNX | Chunk: 112 or higher | Extra: 8192`\\\n",
        "If you're not using a index: `f0: RMVPE_ONNX | Chunk: 96 or higher | Extra: 16384`\\\n",
        "**Don't forget to select your Colab GPU in the GPU field (<b>Tesla T4</b>, for free users)*\n",
        "> Seems that PTH models performance better than ONNX for now, you can still try ONNX models and see if it satisfies you\n",
        "\n",
        "\n",
        "*You can always [click here](https://github.com/YunaOneeChan/Voice-Changer-Settings) to check if these settings are up-to-date*\n",
        "<br><br>\n",
        "\n",
        "---\n",
        "\n",
        "###Always use Colab GPU (**VERY VERY VERY IMPORTANT!**)\n",
        "You need to use a Colab GPU so the Voice Changer can work faster and better\\\n",
        "Use the menu above and click on **Runtime** » **Change runtime** » **Hardware acceleration** to select a GPU (**T4 is the free one**)\n",
        "\n",
        "---\n",
        "\n",
        "<br>\n",
        "\n",
        "# **Credits and Support**\n",
        "Realtime Voice Changer by [w-okada](https://github.com/w-okada)\\\n",
        "Colab files updated by [rafacasari](https://github.com/Rafacasari)\\\n",
        "Recommended settings by [YunaOneeChan](https://github.com/YunaOneeChan)\\\n",
        "Modified again by [Hina](https://huggingface.co/HinaBl)\n",
        "\n",
        "Need help? [AI Hub Discord](https://discord.gg/aihub) » ***#help-realtime-vc***\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "RhdqDSt-LfGr"
      },
      "outputs": [],
      "source": [
        "# @title **[Optional]** Connect to Google Drive\n",
        "# @markdown Using Google Drive can improve load times a bit and your models will be stored, so you don't need to re-upload every time that you use.\n",
        "import os\n",
        "from google.colab import drive\n",
        "\n",
        "if not os.path.exists('/content/drive'):\n",
        "  drive.mount('/content/drive')\n",
        "\n",
        "%cd /content/drive/MyDrive"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "86wTFmqsNMnD",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "# @title **[1]** Clone repository and install dependencies\n",
        "# @markdown This first step will download the latest version of Voice Changer and install the dependencies. **It will take around 2 minutes to complete.**\n",
        "import os\n",
        "import time\n",
        "import subprocess\n",
        "import threading\n",
        "import shutil\n",
        "import base64\n",
        "import codecs\n",
        "\n",
        "from IPython.display import clear_output, Javascript\n",
        "\n",
        "externalgit=codecs.decode('uggcf://tvguho.pbz/j-bxnqn/ibvpr-punatre.tvg','rot_13')\n",
        "rvctimer=codecs.decode('uggcf://tvguho.pbz/uvanoy/eipgvzre.tvg','rot_13')\n",
        "pathloc=codecs.decode('ibvpr-punatre','rot_13')\n",
        "!git clone --depth 1 $externalgit &> /dev/null\n",
        "\n",
        "def update_timer_and_print():\n",
        "    global timer\n",
        "    while True:\n",
        "        hours, remainder = divmod(timer, 3600)\n",
        "        minutes, seconds = divmod(remainder, 60)\n",
        "        timer_str = f'{hours:02}:{minutes:02}:{seconds:02}'\n",
        "        print(f'\\rTimer: {timer_str}', end='', flush=True)  # Print without a newline\n",
        "        time.sleep(1)\n",
        "        timer += 1\n",
        "timer = 0\n",
        "threading.Thread(target=update_timer_and_print, daemon=True).start()\n",
        "\n",
        "# os.system('cls')\n",
        "clear_output()\n",
        "!rm -rf rvctimer\n",
        "!git clone --depth 1 $rvctimer\n",
        "!cp -f rvctimer/index.html $pathloc/client/demo/dist/\n",
        "\n",
        "\n",
        "%cd $pathloc/server/\n",
        "\n",
        "print(\"\\033[92mSuccessfully cloned the repository\")\n",
        "\n",
        "\n",
        "\n",
        "!apt-get install libportaudio2 &> /dev/null --quiet\n",
        "!pip install pyworld onnxruntime-gpu uvicorn faiss-gpu fairseq jedi google-colab moviepy decorator==4.4.2 sounddevice numpy==1.23.5 pyngrok --quiet\n",
        "print(\"\\033[92mInstalling Requirements!\")\n",
        "clear_output()\n",
        "!pip install -r requirements.txt --no-build-isolation --quiet\n",
        "# Maybe install Tensor packages?\n",
        "#!pip install torch-tensorrt\n",
        "#!pip install TensorRT\n",
        "print(\"\\033[92mSuccessfully installed all packages!\")\n",
        "# os.system('cls')\n",
        "clear_output()\n",
        "print(\"\\033[92mFinished, please continue to the next cell\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "#@title #**[Optional]** Upload a voice model (Run this before running the Voice Changer)**[Currently Under Construction]**\n",
        "#@markdown ---\n",
        "import os\n",
        "import json\n",
        "\n",
        "\n",
        "#@markdown #Model Number `(Default is 0)` you can add multiple models as long as you change the number!\n",
        "model_number = \"0\" #@param ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67', '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89', '90', '91', '92', '93', '94', '95', '96', '97', '98', '99', '100', '101', '102', '103', '104', '105', '106', '107', '108', '109', '110', '111', '112', '113', '114', '115', '116', '117', '118', '119', '120', '121', '122', '123', '124', '125', '126', '127', '128', '129', '130', '131', '132', '133', '134', '135', '136', '137', '138', '139', '140', '141', '142', '143', '144', '145', '146', '147', '148', '149', '150', '151', '152', '153', '154', '155', '156', '157', '158', '159', '160', '161', '162', '163', '164', '165', '166', '167', '168', '169', '170', '171', '172', '173', '174', '175', '176', '177', '178', '179', '180', '181', '182', '183', '184', '185', '186', '187', '188', '189', '190', '191', '192', '193', '194', '195', '196', '197', '198', '199']\n",
        "\n",
        "!rm -rf model_dir/$model_number\n",
        "#@markdown ---\n",
        "#@markdown #**[Optional]** Add an icon to the model `(can be any image/leave empty for no image)`\n",
        "icon_link = \"https://cdn.donmai.us/original/8a/92/8a924397e9aac922e94bdc1f28ff978a.jpg\" #@param {type:\"string\"}\n",
        "#@markdown ---\n",
        "icon_link = '\"'+icon_link+'\"'\n",
        "!mkdir model_dir\n",
        "!mkdir model_dir/$model_number\n",
        "#@markdown #Put your model's download link here `(must be a zip file)`\n",
        "model_link = \"https://huggingface.co/HinaBl/Akatsuki/resolve/main/akatsuki_200epoch.zip\"  #@param {type:\"string\"}\n",
        "model_link = '\"'+model_link+'\"'\n",
        "!curl -L $model_link > model.zip\n",
        "\n",
        "\n",
        "# Conditionally set the iconFile based on whether icon_link is empty\n",
        "if icon_link:\n",
        "    iconFile = \"icon.png\"\n",
        "    !curl -L $icon_link > model_dir/$model_number/icon.png\n",
        "else:\n",
        "    print(\"icon_link is empty, so no icon file will be downloaded.\")\n",
        "#@markdown ---\n",
        "\n",
        "\n",
        "!unzip model.zip -d model_dir/$model_number\n",
        "\n",
        "# Checks all the files in model_number and puts it outside of it\n",
        "\n",
        "!mv model_dir/$model_number/*/* model_dir/$model_number/\n",
        "!rm -rf model_dir/$model_number/*/\n",
        "\n",
        "# if theres a folder in the number,\n",
        "# take all the files in the folder and put it outside of that folder\n",
        "\n",
        "\n",
        "#@markdown #**Model Voice Convertion Setting**\n",
        "Tune = 12 #@param {type:\"slider\",min:-50,max:50,step:1}\n",
        "Index = 0 #@param {type:\"slider\",min:0,max:1,step:0.1}\n",
        "#@markdown ---\n",
        "#@markdown #Parameter Option `(Ignore if theres a Parameter File)`\n",
        "Slot_Index = -1 #@param [-1,0,1] {type:\"raw\"}\n",
        "Sampling_Rate = 48000  #@param [32000,40000,48000] {type:\"raw\"}\n",
        "\n",
        "# @markdown #**[Optional]** Parameter file for your voice model\n",
        "#@markdown _(must be named params.json)_ (Leave Empty for Default)\n",
        "param_link = \"\"  #@param {type:\"string\"}\n",
        "if param_link == \"\":\n",
        "    model_dir = \"model_dir/\"+model_number+\"/\"\n",
        "\n",
        "    # Find the .pth and .index files in the model_dir/0 directory\n",
        "    pth_files = [f for f in os.listdir(model_dir) if f.endswith(\".pth\")]\n",
        "    index_files = [f for f in os.listdir(model_dir) if f.endswith(\".index\")]\n",
        "\n",
        "    if pth_files and index_files:\n",
        "        # Take the first .pth and .index file as model and index names\n",
        "        model_name = pth_files[0].replace(\".pth\", \"\")\n",
        "        index_name = index_files[0].replace(\".index\", \"\")\n",
        "    else:\n",
        "        # Set default values if no .pth and .index files are found\n",
        "        model_name = \"Null\"\n",
        "        index_name = \"Null\"\n",
        "\n",
        "    # Define the content for params.json\n",
        "    params_content = {\n",
        "        \"slotIndex\": Slot_Index,\n",
        "        \"voiceChangerType\": \"RVC\",\n",
        "        \"name\": model_name,\n",
        "        \"description\": \"\",\n",
        "        \"credit\": \"\",\n",
        "        \"termsOfUseUrl\": \"\",\n",
        "        \"iconFile\": iconFile,\n",
        "        \"speakers\": {\n",
        "            \"0\": \"target\"\n",
        "        },\n",
        "        \"modelFile\": f\"{model_name}.pth\",\n",
        "        \"indexFile\": f\"{index_name}.index\",\n",
        "        \"defaultTune\": Tune,\n",
        "        \"defaultIndexRatio\": Index,\n",
        "        \"defaultProtect\": 0.5,\n",
        "        \"isONNX\": False,\n",
        "        \"modelType\": \"pyTorchRVCv2\",\n",
        "        \"samplingRate\": Sampling_Rate,\n",
        "        \"f0\": True,\n",
        "        \"embChannels\": 768,\n",
        "        \"embOutputLayer\": 12,\n",
        "        \"useFinalProj\": False,\n",
        "        \"deprecated\": False,\n",
        "        \"embedder\": \"hubert_base\",\n",
        "        \"sampleId\": \"\"\n",
        "    }\n",
        "\n",
        "    # Write the content to params.json\n",
        "    with open(f\"{model_dir}/params.json\", \"w\") as param_file:\n",
        "        json.dump(params_content, param_file)\n",
        "\n",
        "# !unzip model.zip -d model_dir/0/\n",
        "clear_output()\n",
        "print(\"\\033[92mModel with the name of \"+model_name+\" has been Imported!\")\n"
      ],
      "metadata": {
        "cellView": "form",
        "id": "_ZtbKUVUgN3G"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Delete a model\n",
        "#@markdown ---\n",
        "#@markdown Select which slot you want to delete\n",
        "Delete_Slot = \"0\" #@param ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67', '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89', '90', '91', '92', '93', '94', '95', '96', '97', '98', '99', '100', '101', '102', '103', '104', '105', '106', '107', '108', '109', '110', '111', '112', '113', '114', '115', '116', '117', '118', '119', '120', '121', '122', '123', '124', '125', '126', '127', '128', '129', '130', '131', '132', '133', '134', '135', '136', '137', '138', '139', '140', '141', '142', '143', '144', '145', '146', '147', '148', '149', '150', '151', '152', '153', '154', '155', '156', '157', '158', '159', '160', '161', '162', '163', '164', '165', '166', '167', '168', '169', '170', '171', '172', '173', '174', '175', '176', '177', '178', '179', '180', '181', '182', '183', '184', '185', '186', '187', '188', '189', '190', '191', '192', '193', '194', '195', '196', '197', '198', '199']\n",
        "{type:\"slider\",min:0,max:1,step:0.1}\n",
        "\n",
        "!rm -rf model_dir/$Model_Number\n",
        "print(\"\\033[92mSuccessfully removed Model is slot \"+Delete_Slot)\n"
      ],
      "metadata": {
        "id": "P9g6rG1-KUwt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lLWQuUd7WW9U"
      },
      "outputs": [],
      "source": [
        "# @title **[2]** Start Server **using ngrok** (Recommended | **need a ngrok account**)\n",
        "# @markdown This cell will start the server, the first time that you run it will download the models, so it can take a while (~1-2 minutes)\n",
        "\n",
        "# @markdown ---\n",
        "# @markdown You'll need a ngrok account, but **it's free**!\n",
        "# @markdown ---\n",
        "# @markdown **1** - Create a **free** account at [ngrok](https://dashboard.ngrok.com/signup)\\\n",
        "# @markdown **2** - If you didn't logged in with Google or Github, you will need to **verify your e-mail**!\\\n",
        "# @markdown **3** - Click [this link](https://dashboard.ngrok.com/get-started/your-authtoken) to get your auth token, copy it and place it here:\n",
        "from pyngrok import conf, ngrok\n",
        "\n",
        "f0_det= \"rmvpe_onnx\" #@param [\"rmvpe_onnx\",\"rvc\"]\n",
        "Token = 'YOUR_TOKEN_HERE' # @param {type:\"string\"}\n",
        "# @markdown **4** - Still need further tests, but maybe region can help a bit on latency?\\\n",
        "# @markdown `Default Region: us - United States (Ohio)`\n",
        "Region = \"ap - Asia/Pacific (Singapore)\" # @param [\"ap - Asia/Pacific (Singapore)\", \"au - Australia (Sydney)\",\"eu - Europe (Frankfurt)\", \"in - India (Mumbai)\",\"jp - Japan (Tokyo)\",\"sa - South America (Sao Paulo)\", \"us - United States (Ohio)\"]\n",
        "MyConfig = conf.PyngrokConfig()\n",
        "\n",
        "MyConfig.auth_token = Token\n",
        "MyConfig.region = Region[0:2]\n",
        "\n",
        "conf.get_default().authtoken = Token\n",
        "conf.get_default().region = Region[0:2]\n",
        "\n",
        "conf.set_default(MyConfig);\n",
        "\n",
        "# @markdown ---\n",
        "# @markdown If you want to automatically clear the output when the server loads, check this option.\n",
        "Clear_Output = True # @param {type:\"boolean\"}\n",
        "\n",
        "mainpy=codecs.decode('ZZIPFreireFVB.cl','rot_13')\n",
        "\n",
        "import portpicker, socket, urllib.request\n",
        "PORT = portpicker.pick_unused_port()\n",
        "\n",
        "from pyngrok import ngrok\n",
        "# Edited ⏬⏬\n",
        "ngrokConnection = ngrok.connect(PORT)\n",
        "public_url = ngrokConnection.public_url\n",
        "\n",
        "def iframe_thread(port):\n",
        "  while True:\n",
        "      time.sleep(0.5)\n",
        "      sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n",
        "      result = sock.connect_ex(('127.0.0.1', port))\n",
        "      if result == 0:\n",
        "        break\n",
        "      sock.close()\n",
        "  clear_output()\n",
        "  print(\"------- SERVER READY! -------\")\n",
        "  print(\"Your server is available at:\")\n",
        "  print(public_url)\n",
        "  print(\"-----------------------------\")\n",
        "  # display(Javascript('window.open(\"{url}\", \\'_blank\\');'.format(url=public_url)))\n",
        "\n",
        "print(PORT)\n",
        "\n",
        "\n",
        "\n",
        "threading.Thread(target=iframe_thread, daemon=True, args=(PORT,)).start()\n",
        "\n",
        "\n",
        "!python3 $mainpy \\\n",
        "  -p {PORT} \\\n",
        "  --https False \\\n",
        "  --content_vec_500 pretrain/checkpoint_best_legacy_500.pt \\\n",
        "  --content_vec_500_onnx pretrain/content_vec_500.onnx \\\n",
        "  --content_vec_500_onnx_on true \\\n",
        "  --hubert_base pretrain/hubert_base.pt \\\n",
        "  --hubert_base_jp pretrain/rinna_hubert_base_jp.pt \\\n",
        "  --hubert_soft pretrain/hubert/hubert-soft-0d54a1f4.pt \\\n",
        "  --nsf_hifigan pretrain/nsf_hifigan/model \\\n",
        "  --crepe_onnx_full pretrain/crepe_onnx_full.onnx \\\n",
        "  --crepe_onnx_tiny pretrain/crepe_onnx_tiny.onnx \\\n",
        "  --rmvpe pretrain/rmvpe.pt \\\n",
        "  --model_dir model_dir \\\n",
        "  --samples samples.json\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title **[Optional]** Start Server **using localtunnel** (ngrok alternative | no account needed)\n",
        "# @markdown This cell will start the server, the first time that you run it will download the models, so it can take a while (~1-2 minutes)\n",
        "\n",
        "# @markdown ---\n",
        "!npm config set update-notifier false\n",
        "!npm install -g localtunnel\n",
        "print(\"\\033[92mLocalTunnel installed!\")\n",
        "# @markdown If you want to automatically clear the output when the server loads, check this option.\n",
        "Clear_Output = True # @param {type:\"boolean\"}\n",
        "\n",
        "import portpicker, subprocess, threading, time, socket, urllib.request\n",
        "PORT = portpicker.pick_unused_port()\n",
        "\n",
        "from IPython.display import clear_output, Javascript\n",
        "\n",
        "def iframe_thread(port):\n",
        "  while True:\n",
        "      time.sleep(0.5)\n",
        "      sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n",
        "      result = sock.connect_ex(('127.0.0.1', port))\n",
        "      if result == 0:\n",
        "        break\n",
        "      sock.close()\n",
        "  clear_output()\n",
        "  print(\"Use the following endpoint to connect to localtunnel:\", urllib.request.urlopen('https://ipv4.icanhazip.com').read().decode('utf8').strip(\"\\n\"))\n",
        "  p = subprocess.Popen([\"lt\", \"--port\", \"{}\".format(port)], stdout=subprocess.PIPE)\n",
        "  for line in p.stdout:\n",
        "    print(line.decode(), end='')\n",
        "\n",
        "threading.Thread(target=iframe_thread, daemon=True, args=(PORT,)).start()\n",
        "\n",
        "\n",
        "!python3 MMVCServerSIO.py \\\n",
        "  -p {PORT} \\\n",
        "  --https False \\\n",
        "  --content_vec_500 pretrain/checkpoint_best_legacy_500.pt \\\n",
        "  --content_vec_500_onnx pretrain/content_vec_500.onnx \\\n",
        "  --content_vec_500_onnx_on true \\\n",
        "  --hubert_base pretrain/hubert_base.pt \\\n",
        "  --hubert_base_jp pretrain/rinna_hubert_base_jp.pt \\\n",
        "  --hubert_soft pretrain/hubert/hubert-soft-0d54a1f4.pt \\\n",
        "  --nsf_hifigan pretrain/nsf_hifigan/model \\\n",
        "  --crepe_onnx_full pretrain/crepe_onnx_full.onnx \\\n",
        "  --crepe_onnx_tiny pretrain/crepe_onnx_tiny.onnx \\\n",
        "  --rmvpe pretrain/rmvpe.pt \\\n",
        "  --model_dir model_dir \\\n",
        "  --samples samples.json \\\n",
        "  --colab True"
      ],
      "metadata": {
        "cellView": "form",
        "id": "ZwZaCf4BeZi2"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "private_outputs": true,
      "gpuType": "T4"
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
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